共查询到20条相似文献,搜索用时 62 毫秒
1.
In this paper, a temporal resolution reduction transcoding method that transforms an MPEG-4 video bitstream into an H.264
video bitstream is proposed. The block modes and motion vectors in the MPEG-4 bitstream are utilized in the H.264 encoder
for the block mode conversion and motion vector interpolation methods. Four types of motion vector interpolation methods are
proposed in order to avoid the use of brute-force motion estimation in H.264. According to the experimental results, the proposed
methods achieve a 3∼4 times improvement in the computational complexity compared to the cascade pixel-domain transcoding method,
while the PSNR (peak signal to noise ratio) is degraded by 0.2∼0.9 dB depending on the bitrates.
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2.
The H.264 video compression standard supports seven variable block sizes ranging from 4 × 4 to 16 × 16 for one Macro Block
(MB) with 16 × 16 size to conduct motion estimation (ME) and compensation. This new feature achieves significant coding gain
at the cost of huge computation complexity. Dozens of fast mode decision algorithms with fast block size selection have been
proposed to reduce complexity. In this paper, we propose an improved fast block size selection method based on MB movement
characteristic. The Motion Vector (MV) and block residual are employed to analyze the movement characteristic of one MB novelly.
Then the movement characteristic is used to decide whether and how to merge or split the MB for encoding. Experimental results
show that this method speeds up mode decision procedure dramatically with negligible compression performance degradation.
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3.
This paper describes novel transcoding techniques aimed for low-complexity MPEG-2 to H.264/AVC transcoding. An important application
for this type of conversion is efficient storage of broadcast video in consumer devices. The architecture for such a system
is presented, which includes novel motion mapping and mode decision algorithms. For the motion mapping, two algorithms are
presented. Both efficiently map incoming MPEG-2 motion vectors to outgoing H.264/AVC motion vectors regardless of the block
sizes that the motion vectors correspond to. In addition, the algorithm maps motion vectors to different reference pictures,
which is useful for picture type conversion and prediction from multiple reference pictures. We also propose an efficient
rate-distortion optimised macroblock coding mode decision algorithm, which first evaluates candidate modes based on a simple
cost function so that a reduced set of candidate modes is formed, then based on this reduced set, we evaluate the more complex
Lagrangian cost calculation to determine the coding mode. Extensive simulation results show that our proposed transcoder incorporating
the proposed algorithms achieves very good rate-distortion performance with low complexity. Compared with the cascaded decoder-encoder
solution, the coding efficiency is maintained while the complexity is significantly reduced.
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4.
This paper proposes a new approach for shot-based retrieval by optimal matching (OM), which provides an effective mechanism
for the similarity measure and ranking of shots by one-to-one matching. In the proposed approach, a weighted bipartite graph
is constructed to model the color similarity between two shots. Then OM based on Kuhn–Munkres algorithm is employed to compute
the maximum weight of a constructed bipartite graph as the shot similarity value by one-to-one matching among frames. To improve
the speed efficiency of OM, two improved algorithms are also proposed: bipartite graph construction based on subshots and
bipartite graph construction based on the same number of keyframes. Besides color similarity, motion feature is also employed
for shot similarity measure. A motion histogram is constructed for each shot, the motion similarity between two shots is then
measured by the intersection of their motion histograms. Finally, the shot similarity is based on the linear combination of
color and motion similarity. Experimental results indicate that the proposed approach achieves better performance than other
methods in terms of ranking and retrieval capability.
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5.
There are only a few ethical regulations that deal explicitly with robots, in contrast to a vast number of regulations, which
may be applied. We will focus on ethical issues with regard to “responsibility and autonomous robots”, “machines as a replacement
for humans”, and “tele-presence”. Furthermore we will examine examples from special fields of application (medicine and healthcare,
armed forces, and entertainment). We do not claim to present a complete list of ethical issue nor of regulations in the field
of robotics, but we will demonstrate that there are legal challenges with regard to these issues.
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6.
In H.264/AVC, 4 × 4 discrete cosine transform (DCT) is performed on the residual signals after intra prediction for decorrelation.
Actually, residual blocks with different prediction modes exhibit different frequency characteristics. Therefore, the fixed
transform matrix cannot match the energetic distribution of residual signals very well, which degrades the decorrelation performance.
Fortunately, the energetic distributions of residual blocks with the same mode are relatively coincident, which makes it possible
to train a universally good Karhunen–Loève transform (KLT) matrix for each mode. In this paper, an optimal frequency matching
(OFM) algorithm is proposed to train KLT matrices for residual blocks and nine KLT matrices corresponding to nine prediction
modes of 4 × 4 intra blocks are trained. Experimental results show that KLT with trained matrices yields a persistent gain
over H.264 using 4 × 4 DCT with an average peak signal-to-noise ratio (PSNR) enhancement of 0.22dB and a maximum enhancement
of 0.33dB.
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7.
A new parallel normalized exact inverse algorithm is presented for solving sparse symmetric finite element linear systems
on symmetric multiprocessor systems (SMP), based upon an antidiagonal motion approach (“wave”-like pattern) for overcoming
the data dependencies. The proposed algorithm was implemented using OpenMP directives. Numerical results, such as speedups
and efficiency, are presented illustrating the efficient performance on a symmetric multiprocessor computer system, where
the proposed algorithmic solution method achieves good speedups.
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8.
We present the study of a data-driven motion synthesis approach based on a 1D affine image-matching equation. We start by
deriving the relevant properties of the exact matching operator, such as the existence of a singular point. Next, we approximate
such operator by the Green’s function of a second-order differential equation, finding that it leads to a more compelling
motion impression, due to the incorporation of blur. We then proceed to show that, by judicious choice of the matching parameters,
the 1D affine Green’s filter allows the simulation of a broad class of effects, such as zoom-in and zoom-out, and of complex
nonrigid motions such as that of a pulsating heart.
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9.
Accurate 3D registration is a key issue in the Augmented Reality (AR) applications, particularly where are no markers placed
manually. In this paper, an efficient markerless registration algorithm is presented for both outdoor and indoor AR system.
This algorithm first calculates the correspondences among frames using fixed region tracking, and then estimates the motion
parameters on projective transformation following the homography of the tracked region. To achieve the illumination insensitive
tracking, the illumination parameters are solved jointly with motion parameters in each step. Based on the perspective motion
parameters of the tracked region, the 3D registration, the camera’s pose and position, can be calculated with calibrated intrinsic
parameters. A marker-less AR system is described using this algorithm, and the system architecture and working flow are also
proposed. Experimental results with comparison quantitatively demonstrate the correctness of the theoretical analysis and
the robustness of the registration algorithm.
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10.
The main aim of this paper is to accelerate the Chambolle gradient projection method for total variation image restoration.
In the proposed minimization method model, we use the well known Barzilai-Borwein stepsize instead of the constant time stepsize
in Chambolle’s method. Further, we adopt the adaptive nonmonotone line search scheme proposed by Dai and Fletcher to guarantee
the global convergence of the proposed method. Numerical results illustrate the efficiency of this method and indicate that
such a nonmonotone method is more suitable to solve some large-scale inverse problems.
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11.
Listening to music on personal, digital devices whilst mobile is an enjoyable, everyday activity. We explore a scheme for
exploiting this practice to immerse listeners in navigation cues. Our prototype, ONTRACK, continuously adapts audio, modifying
the spatial balance and volume to lead listeners to their target destination. First we report on an initial lab-based evaluation
that demonstrated the approach’s efficacy: users were able to complete tasks within a reasonable time and their subjective
feedback was positive. Encouraged by these results we constructed a handheld prototype. Here, we discuss this implementation
and the results of field-trials. These indicate that even with a low-fidelity realisation of the concept, users can quite
effectively navigate complicated routes.
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12.
A number of mobile applications have emerged that allow users to locate one another. However, people have expressed concerns
about the privacy implications associated with this class of software, suggesting that broad adoption may only happen to the
extent that these concerns are adequately addressed. In this article, we report on our work on P eopleF inder, an application that enables cell phone and laptop users to selectively share their locations with others (e.g. friends,
family, and colleagues). The objective of our work has been to better understand people’s attitudes and behaviors towards
privacy as they interact with such an application, and to explore technologies that empower users to more effectively and
efficiently specify their privacy preferences (or “policies”). These technologies include user interfaces for specifying rules
and auditing disclosures, as well as machine learning techniques to refine user policies based on their feedback. We present
evaluations of these technologies in the context of one laboratory study and three field studies.
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13.
In this paper, we present an Inverse Multi-Objective Robust Evolutionary (IMORE) design methodology that handles the presence
of uncertainty without making assumptions about the uncertainty structure. We model the clustering of uncertain events in
families of nested sets using a multi-level optimization search. To reduce the high computational costs of the proposed methodology
we proposed schemes for (1) adapting the step-size in estimating the uncertainty, and (2) trimming down the number of calls
to the objective function in the nested search. Both offline and online adaptation strategies are considered in conjunction
with the IMORE design algorithm. Design of Experiments (DOE) approaches further reduce the number of objective function calls
in the online adaptive IMORE algorithm. Empirical studies conducted on a series of test functions having diverse complexities
show that the proposed algorithms converge to a set of Pareto-optimal design solutions with non-dominated nominal and robustness
performances efficiently.
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14.
The complexity of group dynamics occurring in small group interactions often hinders the performance of teams. The availability
of rich multimodal information about what is going on during the meeting makes it possible to explore the possibility of providing
support to dysfunctional teams from facilitation to training sessions addressing both the individuals and the group as a whole.
A necessary step in this direction is that of capturing and understanding group dynamics. In this paper, we discuss a particular
scenario, in which meeting participants receive multimedia feedback on their relational behaviour, as a first step towards
increasing self-awareness. We describe the background and the motivation for a coding scheme for annotating meeting recordings
partially inspired by the Bales’ Interaction Process Analysis. This coding scheme was aimed at identifying suitable observable
behavioural sequences. The study is complemented with an experimental investigation on the acceptability of such a service.
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15.
Fast Fourier transforms (FFTs) which are O( N log N) algorithms to compute a discrete Fourier transform (DFT) of size N have been called one of the ten most important algorithms of the twentieth century. However, even though many algorithms
have been developed to speed up the computation the sum of absolute difference (SAD) matching, they are exclusively designed
in the spatial domain. In this paper, we propose a fast frequency algorithm to speed up the process of (SAD) matching. We
use a new approach to approximate the SAD metric by cosine series which can be expressed in correlation terms. These latter
can be computed using FFT algorithms. Experimental results demonstrate the effectiveness of our method when using only the
first correlation terms for block and template matching in terms of accuracy and speed. The proposed algorithm is suitable
for software implementations and has a deterministic execution time unlike the existing fast algorithms for SAD matching.
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16.
This paper describes the simulated car racing competition that was arranged as part of the 2007 IEEE Congress on Evolutionary
Computation. Both the game that was used as the domain for the competition, the controllers submitted as entries to the competition
and its results are presented. With this paper, we hope to provide some insight into the efficacy of various computational
intelligence methods on a well-defined game task, as well as an example of one way of running a competition. In the process,
we provide a set of reference results for those who wish to use the simplerace game to benchmark their own algorithms. The paper is co-authored by the organizers and participants of the competition.
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17.
We provide the complete record of methodology that let us evolve BrilliAnt, the winner of the Ant Wars contest. Ant Wars contestants are virtual ants collecting food on a grid board in the presence
of a competing ant. BrilliAnt has been evolved through a competitive one-population coevolution using genetic programming
and fitnessless selection. In this paper, we detail the evolutionary setup that lead to BrilliAnt’s emergence, assess its
direct and indirect human-competitiveness, and describe the behavioral patterns observed in its strategy.
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18.
To get the maximum benefit from ambient intelligence (AmI), we need to anticipate and react to possible drawbacks and threats
emerging from the new technologies in order to devise appropriate safeguards. The SWAMI project took a precautionary approach
in its exploration of the privacy risks in AmI and sought ways to reduce them. It constructed four “dark scenarios” showing
possible negative implications of AmI, notably for privacy protection. Legal analysis of the depicted futures showed the shortcomings
of the current legal framework in being able to provide adequate privacy protection in the AmI environment. In this paper,
the authors, building upon their involvement in SWAMI research as well as the further advancement of EU privacy analysis,
identify various outstanding issues regarding the legal framework that still need to be resolved in order to deal with AmI
in an equitable and efficacious way. This article points out some of the lacunae in the legal framework and postulates several
privacy-specific safeguards aimed at overcoming them.
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19.
Nowadays data mining plays an important role in decision making. Since many organizations do not possess the in-house expertise
of data mining, it is beneficial to outsource data mining tasks to external service providers. However, most organizations
hesitate to do so due to the concern of loss of business intelligence and customer privacy. In this paper, we present a Bloom
filter based solution to enable organizations to outsource their tasks of mining association rules, at the same time, protect
their business intelligence and customer privacy. Our approach can achieve high precision in data mining by trading-off the
storage requirement.
This research was supported by the USA National Science Foundation Grants CCR-0310974 and IIS-0546027.
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20.
Real-time crowd motion planning requires fast, realistic methods for path planning as well as obstacle avoidance. In a previous
work (Morini et al. in Cyberworlds International Conference, pp. 144–151, 2007), we introduced a hybrid architecture to handle real-time motion planning of thousands of pedestrians. In this article, we
present an extended version of our architecture, introducing two new features: an improved short-term collision avoidance
algorithm, and simple efficient group behavior for crowds. Our approach allows the use of several motion planning algorithms
of different precision for regions of varied interest. Pedestrian motion continuity is ensured when switching between such
algorithms. To assess our architecture, several performance tests have been conducted, as well as a subjective test demonstrating
the impact of using groups. Our results show that the architecture can plan motion in real time for several thousands of characters.
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